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      Zerumbone Protects Rats from Collagen-Induced Arthritis by Inhibiting Oxidative Outbursts and Inflammatory Cytokine Levels

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          Abstract

          Rheumatoid arthritis (RA) is an immunocompromised disorder characterized by a marked increase in the synthesis of inflammatory molecules that stimulates the destruction of bones and cartilage. The conventional treatment modalities for RA are associated with adverse side effects and lack sensitivity, suggesting an immediate demand for alternate beneficial therapeutic remedies. The current study sought to understand more about zerumbone’s anti-inflammatory properties in diagnosing collagen-induced arthritis (CIA) in experimental animals. The current study observed that zerumbone reduced clinical severity in CIA-induced animals compared to healthy animals. Zerumbone administration significantly decreased ( p < 0.001) the concentration of SOD, CAT, GR, and GSH in treatment groups. Zerumbone administration drove down significantly ( p < 0.001) the concentration of inflammatory cytokine molecules. Zerumbone was effective in bringing significant changes in levels of MPO, NO, LDH, MMP-8, and ELA. The therapeutic potential of zerumbone was found to be associated with reduced joint destruction and restored normal histology in the cartilage and tissue. Adsorption, distribution, metabolism, excretion, and toxicity studies were used to determine the druglike properties of zerumbone. ProTox-II studies revealed that zerumbone did not possess toxic properties like hepatotoxicity, immunotoxicity, carcinogenicity, mutagenicity, and cytotoxicity. Therefore, the present study evaluated the therapeutic properties of zerumbone in CIA animal models.

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          SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules

          To be effective as a drug, a potent molecule must reach its target in the body in sufficient concentration, and stay there in a bioactive form long enough for the expected biologic events to occur. Drug development involves assessment of absorption, distribution, metabolism and excretion (ADME) increasingly earlier in the discovery process, at a stage when considered compounds are numerous but access to the physical samples is limited. In that context, computer models constitute valid alternatives to experiments. Here, we present the new SwissADME web tool that gives free access to a pool of fast yet robust predictive models for physicochemical properties, pharmacokinetics, drug-likeness and medicinal chemistry friendliness, among which in-house proficient methods such as the BOILED-Egg, iLOGP and Bioavailability Radar. Easy efficient input and interpretation are ensured thanks to a user-friendly interface through the login-free website http://www.swissadme.ch. Specialists, but also nonexpert in cheminformatics or computational chemistry can predict rapidly key parameters for a collection of molecules to support their drug discovery endeavours.
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            Lead- and drug-like compounds: the rule-of-five revolution.

            Citations in CAS SciFinder to the rule-of-five (RO5) publication will exceed 1000 by year-end 2004. Trends in the RO5 literature explosion that can be discerned are the further definitions of drug-like. This topic is explored in terms of drug-like physicochemical features, drug-like structural features, a comparison of drug-like and non-drug-like in drug discovery and a discussion of how drug-like features relate to clinical success. Physicochemical features of CNS drugs and features related to CNS blood-brain transporter affinity are briefly reviewed. Recent literature on features of non-oral drugs is reviewed and how features of lead-like compounds differ from those of drug-like compounds is discussed. Most recently, partly driven by NIH roadmap initiatives, considerations have arisen as to what tool-like means in the search for chemical tools to probe biology space. All these topics frame the scope of this short review/perspective.: © 2004 Elsevier Ltd . All rights reserved.
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              admetSAR 2.0: web-service for prediction and optimization of chemical ADMET properties

              admetSAR was developed as a comprehensive source and free tool for the prediction of chemical ADMET properties. Since its first release in 2012 containing 27 predictive models, admetSAR has been widely used in chemical and pharmaceutical fields. This update, admetSAR 2.0, focuses on extension and optimization of existing models with significant quantity and quality improvement on training data. Now 47 models are available for either drug discovery or environmental risk assessment. In addition, we added a new module named ADMETopt for lead optimization based on predicted ADMET properties.
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                Author and article information

                Journal
                ACS Omega
                ACS Omega
                ao
                acsodf
                ACS Omega
                American Chemical Society
                2470-1343
                10 January 2023
                24 January 2023
                : 8
                : 3
                : 2982-2991
                Affiliations
                []Department of Pharmacology & Toxicology, College of Pharmacy, Prince Sattam Bin Abdulaziz University , P.O. Box 173, Al-Kharj 11942, Saudi Arabia
                []Division of Veterinary Biochemistry, Faculty of Veterinary Science and Animal Husbandry, SKUAST-Kashmir , Shuhama, Alusteng, Srinagar, Jammu and Kashmir 190006, India
                [§ ]Mycoplasma Laboratory, Faculty of Veterinary Sciences and Animal Husbandry , Shuhama, Alusteng, Srinagar, Jammu and Kashmir 190006, India
                []Department of Statistics, University of Kashmir , Srinagar, Jammu and Kashmir 190006, India
                []Department of Clinical Pharmacy, College of Pharmacy, King Saud University , Riyadh 11451, Saudi Arabia
                Author notes
                Author information
                https://orcid.org/0000-0002-9995-6576
                Article
                10.1021/acsomega.2c05749
                9878628
                36713739
                b9570cce-7b11-4d3c-921f-75b4ac3dc674
                © 2023 The Authors. Published by American Chemical Society

                Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works ( https://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 05 September 2022
                : 22 December 2022
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                ao2c05749

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